@article{ART003096320},
author={Hyeok-Don Kwon and Kwon Jung-Hyok and SOLBEE LEE and EUIJIK KIM},
title={LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information},
journal={Journal of Internet of Things and Convergence},
issn={2466-0078},
year={2024},
volume={10},
number={3},
pages={57-64}
TY - JOUR
AU - Hyeok-Don Kwon
AU - Kwon Jung-Hyok
AU - SOLBEE LEE
AU - EUIJIK KIM
TI - LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information
JO - Journal of Internet of Things and Convergence
PY - 2024
VL - 10
IS - 3
PB - The Korea Internet of Things Society
SP - 57
EP - 64
SN - 2466-0078
AB - In this paper, we propose a Line-of-Sight (LoS)/Non-Line-of-Sight (NLoS) identification- based Human Activity Recognition (HAR) system using Channel State Information (CSI) to improve the accuracy of HAR, which dynamically changes depending on the reception environment. to consider the reception environment of HAR system, the proposed system includes three operational phases: Preprocessing phase, Classification phase, and Activity recognition phase. In the preprocessing phase, amplitude is extracted from CSI raw data, and noise in the extracted amplitude is removed. In the Classification phase, the reception environment is categorized into LoS and NLoS. Then, based on the categorized reception environment, the HAR model is determined based on the result of the reception environment categorization. Finally, in the activity recognition phase, human actions are classified into sitting, walking, standing, and absent using the determined HAR model. To demonstrate the superiority of the proposed system, an experimental implementation was performed and the accuracy of the proposed system was compared with that of the existing HAR system. The results showed that the proposed system achieved 16.25% higher accuracy than the existing system
KW - Machine learning;Reception environment categorization;Human activity recognition;Channel state information;LoS/NLoS identification
DO -
UR -
ER -
Hyeok-Don Kwon, Kwon Jung-Hyok, SOLBEE LEE and EUIJIK KIM. (2024). LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information. Journal of Internet of Things and Convergence, 10(3), 57-64.
Hyeok-Don Kwon, Kwon Jung-Hyok, SOLBEE LEE and EUIJIK KIM. 2024, "LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information", Journal of Internet of Things and Convergence, vol.10, no.3 pp.57-64.
Hyeok-Don Kwon, Kwon Jung-Hyok, SOLBEE LEE, EUIJIK KIM "LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information" Journal of Internet of Things and Convergence 10.3 pp.57-64 (2024) : 57.
Hyeok-Don Kwon, Kwon Jung-Hyok, SOLBEE LEE, EUIJIK KIM. LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information. 2024; 10(3), 57-64.
Hyeok-Don Kwon, Kwon Jung-Hyok, SOLBEE LEE and EUIJIK KIM. "LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information" Journal of Internet of Things and Convergence 10, no.3 (2024) : 57-64.
Hyeok-Don Kwon; Kwon Jung-Hyok; SOLBEE LEE; EUIJIK KIM. LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information. Journal of Internet of Things and Convergence, 10(3), 57-64.
Hyeok-Don Kwon; Kwon Jung-Hyok; SOLBEE LEE; EUIJIK KIM. LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information. Journal of Internet of Things and Convergence. 2024; 10(3) 57-64.
Hyeok-Don Kwon, Kwon Jung-Hyok, SOLBEE LEE, EUIJIK KIM. LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information. 2024; 10(3), 57-64.
Hyeok-Don Kwon, Kwon Jung-Hyok, SOLBEE LEE and EUIJIK KIM. "LoS/NLoS Identification-based Human Activity Recognition System Using Channel State Information" Journal of Internet of Things and Convergence 10, no.3 (2024) : 57-64.
